Abstract
This paper describes a new approach to natural-language chunking using genetic algorithms. This uses previously captured training information to guide the evolution of the model. In addition, a multi-objective optimization strategy is used to produce unique quality values for objective functions involving the internal and the external quality of chunking. Experiments and the main results obtained using the model and state-of-the-art approaches are discussed.
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© 2010 Springer-Verlag London
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Atkinson, J., Matamala, J. (2010). Chunking Natural Language Texts using Evolutionary Methods*. In: Bramer, M., Ellis, R., Petridis, M. (eds) Research and Development in Intelligent Systems XXVI. Springer, London. https://doi.org/10.1007/978-1-84882-983-1_20
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DOI: https://doi.org/10.1007/978-1-84882-983-1_20
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Online ISBN: 978-1-84882-983-1
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